AI in marketing

8 Examples of AI in Marketing

In Social Media Strategy by Eric VidalLeave a Comment

Artificial intelligence is revolutionizing dozens of industries, and the marketing industry is no different. Marketers are using AI to improve ad targeting, generate more leads, provide customer service, and improve website design. The following eight examples show how uses of AI in marketing today and what we will likely see over the next five years.

1. Search Engines

Back in November of 2015, Google officially confirmed they had implemented a machine learning AI called RankBrain into their query-filtering process. Rankbrain learns from each user query and applies these learnings to each successive query.

Machine learning AI in marketing helps Google recognize the natural language people use when they type online and then use this information to provide the most relevant search results. The goal is to optimize the user experience by providing nothing but the highest quality information.

RankBrain will play a large role in processing voice search queries as the popularity of home assistants like Alexa and Google Home continue to rise.

2. Website Design 

Designing a website for your brand is a painstaking process. The Grid aims to take the pain out of website design with their AI web designer. You give “Molly” the information you want on your site, and you get a serviceable website within hours.

Plans for this service start as low as $100 per year for a single website. Instead of paying for a web designer, you can save yourself thousands of dollars by using AI to take care of your site.

3. Content Creation

Would you read an article written by AI? If you follow sports or stocks, there is a good chance you already have. In the year 2016, an article-writing AI called Wordsmith cranked out 1.5 billion pieces of content.

There is good news for human writers, though. Wordsmith and similar content-creation AI can only write articles based on hard stats. It can write hard news stories, sports stories, and financial reports, but cannot write features and opinion pieces. Still, AI-generated content will continue to be a major tool for content marketers within these niches. 

4. Predictive Customer Service

What if you could know what your customers want before they ask? Predictive analytics makes this dream a reality.

Servicing existing customers is cheaper than acquiring new ones. Predictive customer service allows marketers to create personalized micro-campaigns for each customer. This type of AI in marketing draws on its ever-growing database of customer behavior to serve the right information at the right time.

5. Chatbots

Messaging apps like Facebook Messenger and Whatsapp are hot amongst younger millennials and older members of Gen Z, and Slack dominates the professional messaging space. With the popularity of such apps, savvy marketers are using chatbots to provide customer service through these apps.


Many companies also have chatbots on their website. These bots answer common customer questions by using machine learning to draw upon past customer questions. In other words, chatbots get smarter with each conversation.

6. Speech Recognition

As I mentioned earlier, smart home assistants are currently dominating the market. Voice search will become increasingly important to marketers as more users become comfortable with asking Alexa to search for information instead of typing it into a search bar.

The first marketers to figure out how to best optimize their content for voice search will gain a huge competitive advantage. 

7. Ad Targeting

Have you ever searched for a product on Google, only to visit a website later on and have an ad for the product served to you in the sidebar? This is the work of ad-targeting AI.

Ad-targeting AI scores the performance of each ad and uses this data to serve the ads shown to convert best. It takes the guesswork out of targeting an ad campaign.

8. Dynamic Pricing

Discounts have always been a great way to increase sales. The problem is customers who would have paid full price end up paying less, which means fewer profits.

Dynamic pricing eliminates this problem by using machine learning to only send discounts to customers who need it to make a purchasing decision. Dynamic pricing also allows you to send different discounts to different types of customers, which allows you to test multiple promotions at once.

These eight examples are just some of the many uses of AI in marketing. It will be interesting to see how these marketing trends develop as AI becomes more intelligent.

This post about AI in marketing originally appeared at The Marketing Scope.